Iurova M V, Chagovets V V, Pavlovich S V, Starodubtseva N L, Khabas G N, Chingin K S, Tokareva A O, Sukhikh G T, Frankevich V E
Federal State Budget Institution, National Medical Research Center for Obstetrics, Gynecology and Perinatology named after Academician V.I. Kulakov, Ministry of Healthcare of the Russian Federation, Moscow, Russia.
Federal State Autonomous Educational Institution of Higher Education, I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), Moscow, Russia.
Front Mol Biosci. 2022 Apr 14;9:770983. doi: 10.3389/fmolb.2022.770983. eCollection 2022.
Epithelial ovarian cancer (OC) ranks first in the number of deaths among diseases of the female reproductive organs. Identification of OC at early stages is highly beneficial for the treatment but is highly challenging due to the asymptomatic or low-symptom disease development. In this study, lipid extracts of venous blood samples from 41 female volunteers, including 28 therapy-naive patients with histologically verified high-grade serous ovarian cancer at different stages (5 patients with I-II stages; 23 patients with III-IV stages) and 13 apparently healthy women of reproductive age, were profiled by high-performance liquid chromatography mass spectrometry (HPLC-MS). Based on MS signals of 128 differential lipid species with statistically significant level variation between the OC patients and control group, an OPLS-DA model was developed for the recognition of OC with 100% sensitivity and specificity = 0.87 and Q = 0.80. The second OPLS-DA model was developed for the differentiation between I-II OC stages and control group with = 0.97 and Q = 0.86 based on the signal levels of 108 differential lipid species. The third OPLS-DA model was developed for the differentiation between I-II OC stages and III-IV stages based on the signal levels of 99 differential lipid species. Various lipid classes (diglycerides, triglycerides, phosphatidylchlorines, ethanolamines, sphingomyelins, ceramides, phosphatidylcholines and phosphoinositols) in blood plasma samples display distinctly characteristic profiles in I-II OC, which indicates the possibility of their use as marker oncolipids in diagnostic molecular panels of early OC stages. Our results suggest that lipid profiling by HPLC-MS can improve identification of early-stage OC and thus increase the efficiency of treatment.
上皮性卵巢癌（OC）在女性生殖器官疾病的死亡人数中排名第一。早期识别OC对治疗非常有益，但由于疾病发展无症状或症状轻微，极具挑战性。在本研究中，通过高效液相色谱质谱联用仪（HPLC-MS）对41名女性志愿者静脉血样的脂质提取物进行了分析，其中包括28例未经治疗的不同阶段组织学确诊的高级别浆液性卵巢癌患者（5例I-II期患者；23例III-IV期患者）和13名明显健康的育龄妇女。基于128种差异脂质种类的质谱信号，其在OC患者和对照组之间存在统计学显著水平差异，建立了一个OPLS-DA模型用于识别OC，灵敏度和特异性均为100%（R2 = 0.87，Q = 0.80）。基于108种差异脂质种类的信号水平，建立了第二个OPLS-DA模型用于区分I-II期OC和对照组（R2 = 0.97，Q = 0.86）。基于99种差异脂质种类的信号水平，建立了第三个OPLS-DA模型用于区分I-II期OC和III-IV期OC。血浆样本中的各种脂质类别（甘油二酯、甘油三酯、磷脂酰氯、乙醇胺、鞘磷脂、神经酰胺、磷脂酰胆碱和磷酸肌醇）在I-II期OC中显示出明显的特征图谱，这表明它们有可能作为早期OC阶段诊断分子面板中的肿瘤脂质标志物。我们的结果表明，通过HPLC-MS进行脂质分析可以改善早期OC的识别，从而提高治疗效率。
